Search Results - (( program implementation genetic algorithm ) OR ( code classification problem algorithm ))
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Using genetic algorithms to optimise land use suitability
Published 2012“…In this study, under environmentfriendliness objective, based on multi-agent genetic algorithms, was developed a geospatial model for the land use allocation. …”
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Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms
Published 2008“…This algorithm has been tested and implemented successfully via a dual beam optical scanning system.…”
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Genetic algorithm based for optimizing filter design / Rohana Awang Ahmed
Published 2000“…The conventional filter design technique is adapted in writing a MATLAB program using the Signal Processing Toolbox. GA is then implemented using the Genetic Algorithm Toolbox (GAOT). …”
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Parallel distributed genetic algorithm development based on microcontrollers framework
Published 2023Conference paper -
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Application of genetic algorithm and JFugue in an evolutionary music generator
Published 2025“…This project explores the application of Genetic Algorithms (GA) with JFugue, which is a Java-based music programming library to develop an Evolutionary Music Generator. …”
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Network reconfiguration and control for loss reduction using genetic algorithm
Published 2010“…Two selection methods that are used in Genetic Algorithm are the roulette wheel and tournament selections. …”
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Intelligent agent for e-commerce using genetic algorithm / Kok Sun Sun
Published 2000“…This system is achieved using the Genetic Algorithm which is capable of performing information retrieval and learning algorithm. …”
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A genetic algorithm for solving single level lotsizing problems
Published 2003“…In our implementation, a lot-sizing population-generating heuristic is used to feed chromosomes to a genetic algorithm with operators specially designed for lot-sizing problems. …”
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Object-Oriented Programming semantics representation utilizing agents
Published 2011“…Novices tend to refer to source codes examples and adapt the source codes to the problem given in their assignments. …”
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Scene classification for aerial images based on CNN using sparse coding technique
Published 2017“…Recent developments include several approaches and numerous algorithms address the task. This article proposes a convolutional neural network (CNN) approach that utilizes sparse coding for scene classification applicable for HRRS unmanned aerial vehicle (UAV) and satellite imagery. …”
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Maldroid- attribute selection analysis for malware classification
Published 2019“…Hence, the objective of this paper is to find the most effective and efficient attribute selection and classification algorithm in malware detection. Moreover, in order to get the best combination between attribute selection and classification algorithm, eight attributes selection and seven categories machine learning algorithm are applied in this study. …”
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Scene classification for aerial images based on CNN using sparse coding technique
Published 2023Article -
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Dual-head marking performance optimisation via evolutionary solutions
Published 2023“…The representation approach has been implemented via computer program in order to achieve optimised marking performance. …”
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An approach for cross-site scripting detection and removal based on genetic algorithms.
Published 2014“…The proposed approach is, so far, only implemented and validated on Java-based Web applications, although it can be implemented in other programming languages with slight modifications. …”
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A new domain specific scripting language for automated machine learning pipeline
Published 2019“…However, in respond to the implementation difficulty, there exists a limited software tool that support easy implementation for automated machine learning based on Genetic Programming. …”
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Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation
Published 2023Conference paper -
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Predictive Analytics in Genetic Engineering as an Optimization Problem
Published 2024“…Also, the predictive outcomes of the computational simulation that was implemented in Python programming indicate that these local cultivars are developing drought-tolerant genetic variability. …”
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